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Research on fault diagnosis technology of simulated altitude test facility based on multi-optimization strategy, real-time data transfer, and the M-H attention-RF algorithm

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Abstract

The simulated altitude test facility, as an important means to verify the performance, characteristics, and evaluation result criteria of aero-engines, has a pivotal engineering significance in the process of aero-engine development and promotion of application. In order to cope with the drawbacks of traditional techniques for experimental processes, this paper proposes the real-time data extraction and transfer techniques with multiple optimization strategies and the fault diagnosis technology of simulated altitude test facility with an improved optimization algorithm is propose, Firstly, the optimization strategy based on peak shaving + peak fast processing and token bucket instructions with multi-threaded parallel processing flow allocation call logic is used to realize the test data for fast extraction and migration demand, and then the overall data transfer function is optimized in granularity improvement schemes by using the abstraction optimization strategy mechanism based on Direct Routing mode to maximise real-time targets while ensuring correspondence and completeness of test data. Finally, the random forest algorithm with Multi-Head Attention optimization is used to implement the diagnostic technology research of the simulated altitude test facility under two scenarios under the data-driven mode, and the analytical comparison and validation results with the unimproved and optimized Random Forest algorithm are given. The results indicate that the amount of test data synchronization reaches 300 + lines per second, the accuracy of fault diagnosis identification is increased by 30% at the highest degree, and the proposed improvement research has a very high degree of application value and innovativeness.

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Data availability

The data that support the findings of this study are available from [China Gas Turbine Establishment] but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of [China Gas Turbine Establishment].

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Authors and Affiliations

  1. Northwestern Polytechnical University, Xian, 710000, People’s Republic of China

    Qifan Zhou, Yingqing Guo, Wanli Zhao, Kejie Xu, Kun Wang & Zhenglong Wu

  2. Xi’an Institute of Modern Control Technology, Xian, 710000, People’s Republic of China

    Hao Sun

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  1. Qifan Zhou
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Correspondence to Qifan Zhou.

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Zhou, Q., Guo, Y., Zhao, W. et al. Research on fault diagnosis technology of simulated altitude test facility based on multi-optimization strategy, real-time data transfer, and the M-H attention-RF algorithm. Multimed Tools Appl 83, 28729–28760 (2024). https://doi.org/10.1007/s11042-023-16738-3

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